In early cancer diagnosis, extracellular vesicles (EVs) are more advantageous than circulating tumor cells due to their smaller size, greater stability, and enhanced tissue penetration. These qualities lead to higher EV concentrations in body fluids,...
Quantum transport-based DNA sequencing is emerging as a promising technique in genetic analysis, offering fast, precise, and scalable decoding of genetic information, holding significant potential for applications in human biology and personalized me...
This study proposes a method for detecting trace quinolone antibiotics in milk using a ternary composite surface-enhanced Raman spectroscopy (SERS) substrate. It combines chemometric algorithms and deep learning models to achieve qualitative and quan...
Laser desorption ionization mass spectrometry (LDI-MS) is a critical platform for high-throughput nontargeted metabolomics analysis in clinical diagnosis. However, traditional organic matrices inherently suffer from background interference in the low...
Solid-state nanopore and nanochannel biosensors have revolutionized protein detection by offering label-free, highly sensitive analyses. Traditional sensing systems (1st and 2nd stages) primarily focus on inner wall (IW) interactions, facing challeng...
Multimodal cancer therapies are often required for progressive cancers due to the high persistence and mortality of the disease and the negative systemic side effects of traditional therapeutic methods. Thus, the development of less invasive modaliti...
This study explores the separation and optimization of molybdenum (Mo) from mixed mineral acids derived from semiconductor industry waste streams with tributyl phosphate (TBP) by implementing machine learning (ML) models. Considerable experimental te...
Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing pl...
Neuromorphic computing enables efficient processing of data-intensive tasks, but requires numerous artificial synapses and neurons for certain functions, which leads to bulky systems and energy challenges. Achieving functionality with fewer synapses ...
Interdisciplinary sciences, computational life sciences
Jul 24, 2023
Breast cancer is commonly diagnosed with mammography. Using image segmentation algorithms to separate lesion areas in mammography can facilitate diagnosis by doctors and reduce their workload, which has important clinical significance. Because large,...
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